Paper: A convex relaxation for weakly supervised relation extraction

ACL ID D14-1166
Title A convex relaxation for weakly supervised relation extraction
Venue Conference on Empirical Methods in Natural Language Processing
Session Main Conference
Year 2014

A promising approach to relation extrac- tion, called weak or distant supervision, exploits an existing database of facts as training data, by aligning it to an unla- beled collection of text documents. Using this approach, the task of relation extrac- tion can easily be scaled to hundreds of different relationships. However, distant supervision leads to a challenging multi- ple instance, multiple label learning prob- lem. Most of the proposed solutions to this problem are based on non-convex formu- lations, and are thus prone to local min- ima. In this article, we propose a new approach to the problem of weakly su- pervised relation extraction, based on dis- criminative clustering and leading to a convex formulation. We demonstrate that our approach outperforms state-of-the-art methods on...